/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.spark.sql.execution.datasources.v2.state.utils

import org.apache.spark.sql.AnalysisException
import org.apache.spark.sql.types.{DataType, StructType}

object SchemaUtil {
  def getSchemaAsDataType(schema: StructType, fieldName: String): DataType = {
    schema.getFieldIndex(fieldName) match {
      case Some(idx) => schema(idx).dataType
      case _ => throw new AnalysisException(
        errorClass = "_LEGACY_ERROR_TEMP_3074",
        messageParameters = Map(
          "fieldName" -> fieldName,
          "schema" -> schema.toString()))
    }
  }
}
